{"id":"W2133689684","doi":"10.1016/j.cageo.2011.01.009","title":"Exploring pseudo- and chaotic random Monte Carlo simulations","year":2011,"lang":"en","type":"article","venue":"Computers & Geosciences","topic":"Scientific Research and Discoveries","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary; Pacific Institute for the Mathematical Sciences","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Monte Carlo method; Statistical physics; Chaotic; Computer science; Geology; Statistics; Mathematics; Physics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001510676,0.0004760167,0.0008991473,0.001055166,0.0009473979,0.00158182,0.001468402,0.001765125,0.003654219],"category_scores_gemma":[0.01247362,0.0007947016,0.0008245159,0.000742804,0.00190819,0.002215937,0.001632473,0.001070094,0.0001840811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001030458,"about_ca_system_score_gemma":0.001027369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004796412,"about_ca_topic_score_gemma":0.003478391,"domain_scores_codex":[0.9994379,0.000342495,0.00001925555,0.00004560459,0.00009373871,0.00006092637],"domain_scores_gemma":[0.991942,0.006647701,0.0004293976,0.0003706841,0.0003125583,0.0002976852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003850505,0.00002711552,0.0008594319,0.00002627653,0.00002799478,0.00006150415,0.00005463546,0.9152442,0.0001874332,0.08231288,0.000202658,0.0009573316],"study_design_scores_gemma":[0.000007449867,0.000004386749,0.00006259233,0.000002407521,0.000003006283,0.000006180835,0.000006539124,0.984697,0.00003714787,0.01508194,0.00008834344,0.000003016337],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7143303,0.0005686982,0.2554035,0.00173953,0.0001409565,0.00009692262,0.000232859,0.000361959,0.02712536],"genre_scores_gemma":[0.9753388,0.0001666887,0.0221817,0.0001146497,0.00005649566,0.0000641545,0.0001122495,0.00008559854,0.001879662],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004796412,"threshold_uncertainty_score":0.01222456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1335888058479745,"score_gpt":0.2740260743839104,"score_spread":0.1404372685359359,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}